Google DeepMind has unveiled Genie, a text-to-video game model that can turn a description, sketch, or photo into a playable 2D platform video game. While limited to one frame per second, the model eliminates the need for input actions, learning from video footage alone. Genie’s potential extends to virtual environments and robotics, showcasing possible advancements…

Generative AI, driven by OpenAI’s ChatGPT, is revolutionizing businesses with its potential in content creation, translation, and more. Executives foresee AI-driven disruptions, but face challenges including insufficient IT capabilities and non-IT factors such as regulatory risks and skills. As companies aim to deploy generative AI widely, they must address these obstacles to succeed.

The rapidly advancing field of Artificial Intelligence (AI) encompasses technologies like generative AI, deep neural networks, and Large Language Models. It has significant societal impacts in production, health, finance, and education. A recent study proposes regulating the computational resources for AI research to maximize benefits, minimize threats, and ensure equitable access to AI technologies while…

Adversarial attacks pose a significant challenge to Language Models (LLMs), potentially compromising their integrity and reliability. A new research framework targets vulnerabilities in LMs, proposing innovative strategies to counter adversarial tactics and fortify their security. The study emphasizes the importance of proactive and security-centric approaches in developing LLMs. [Word count: 50]

LexC-Gen, a method proposed by researchers at Brown University, addresses data scarcity in low-resource languages using bilingual lexicons and large language models (LLMs). It generates labeled task data for low-resource languages by leveraging LLMs and bilingual lexicons, achieving performance comparable to gold data in sentiment analysis and topic classification tasks. The method offers promise in…

Artificial intelligence is advancing with the integration of multimodal capabilities into large language models (LLMs), revolutionizing how machines understand and interact with the world. Fudan University researchers and collaborators introduced AnyGPT, an innovative LLM that processes multiple modalities of data, showcasing its potential to transform AI applications across various domains. [50 words]

BioBRIDGE is a parameter-efficient learning framework developed by researchers at the University of Illinois Urbana-Champaign and Amazon AWS AI for biomedical research. It unifies independently trained unimodal foundation models (FMs) using Knowledge Graphs (KGs), showcasing impressive generalization ability and potential impact on diverse cross-modal prediction tasks and drug discovery in the biomedical field.

Reka’s state-of-the-art multimodal and multilingual language model, Reka Flash, performs exceptionally on various benchmarks of LLM with just 7B trainable parameters. It competes with leading models on language and vision tasks. Reka Edge, with limited resources, excels in local deployments, outperforming comparable models. Both models give tough competition to existing state-of-the-art LLMs.

Magika is an AI-based file-type detection tool driven by deep learning, offering precise identification within milliseconds and achieving over 99% precision and recall on a diverse dataset. It supports batching for faster processing, provides trustworthy predictions with customizable error tolerance, and aims for continuous improvements. Magika enhances user safety and security, marking a significant advancement…

Research from Meta introduces TestGen-LLM, utilizing Large Language Models to automatically improve human-written test suites, addressing issues with LLM hallucinations. The tool applies filters to ensure test class improvements, providing efficacy and implementation for real-world use cases. TestGen-LLM demonstrated its effectiveness during Meta’s test-a-thons, showing significant improvements and successful production deployment.